Do you mean to say Zed wasn't vibe coded? There's actually another comment on this post describing how someone is using Opus 4.5 to work on Zed. Given how forward the AI features are in Zed I'd be surprised if the team wasn't also embracing it internally.
It's a fair question how much AI is accelerating the development of Zed, but I can say that I've been impressed with the speed they are shipping at.
Indeed it wasn't vibe coded, using LLMs to iterate over a mature and well structured codebase is another thing and won't obliterate the existince of software programmers
My tool can read stdin, send it to an LLM, and do a couple nice things with the reply. Not exactly RAG, but most man pages fit into the context window so it's okay.
Older cars don't have these systems. Also they are easy to bypass with a dummy buckle. There are counties where seatbelt usage is far less common than the US.
As others have mentioned, a firewall might have been useful in restricting outbound connections to limit the usefulness of the machine to the hacker after the breach.
An inbound firewall can only help protect services that aren't meant to be reachable on the public internet. This service was exposed to the internet intentionally so a firewall wouldn't have helped avoid the breach.
The lesson to me is that keeping up with security updates helps prevent publicly exposed services from getting hacked.
On Linux, the default init program is usually systemd. The main job of the default init program is typically to be a process manager. That is, it starts other programs and can restart them if they crash. Since it's the first process to start (PID 1), if it exits the kernel can't continue and will panic, usually followed by a reboot.
Containers work similarly, except that they don't take the whole system down when their PID 1 exits. That's why containers often don't have a process manager inside, but Linux based operating systems do.
The pdf describes how they did "continued pre-training" and then post training to make 3.2. I guess what's missing is the full pre-training that absorbs most date sensitive knowledge. That's probably also the reason that the versions are 3.x still.
There are a number of free and cheap LLM options to experiment with. Google offers a decent free plan for Gemini (get some extra Google accounts). Groq has a free tier including some good open weight models. There's also free endpoints on OpenRouter that are limited but might be useful for long running background agents. DeepSeek v3.2, Qwen3, Kimi K2, and GLM 4.6 are all good choices for cheap and capable models.
Local models are generally not a shortcut to cheap and effective AI. It's a fun thing to explore though.
It's a fair question how much AI is accelerating the development of Zed, but I can say that I've been impressed with the speed they are shipping at.
reply